CANT-HYD: A curated database of phylogeny-derived Hidden Markov Models for annotation of marker genes involved in hydrocarbon degradation

Abstract

Discovery of microbial hydrocarbon degradation pathways has traditionally relied on laboratory isolation and characterization of microorganisms. Although many metabolic pathways for hydrocarbon degradation have been discovered, the absence of tools dedicated to their annotation makes it difficult to identify the relevant genes and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Furthermore, sequence homology between hydrocarbon degradation genes and genes with other functions often results in misannotation. A tool that systematically identifies hydrocarbon metabolic potential is therefore needed. We present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database containing HMMs of 37 marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we show that hydrocarbon metabolic potential is widespread in the tree of life and identify understudied or overlooked hydrocarbon degradation potential in many phyla. We also demonstrate scalability by analyzing large metagenomic datasets for the prediction of hydrocarbon utilization in diverse environments. To the best of our knowledge, CANT-HYD is the first comprehensive tool for robust and accurate identification of marker genes associated with aerobic and anaerobic hydrocarbon degradation.

Geological processes mediate a microbial dispersal loop in the deep biosphere

“…3 and table S7) and encoded glycyl radical enzymes related to alkylsuccinate synthases proposed to mediate anaerobic alkane biodegradation via addition to fumarate ( 34 , 35 ). Using newly developed hidden Markov models for annotating alkylsuccinate synthases ( 36 ), putative assA gene sequences in thermophilic spores are shown here to diverge from canonical assA found in mesophilic Proteobacteria (fig. S5).…”

“…Metabolic pathways were identified using KEGG Decoder ( 69 ) to parse genes annotated with KEGG Orthology using BlastKOALA ( 70 ). Hydrocarbon degradation genes were additionally annotated using CANT-HYD ( 36 ) following gene predictions made using Prodigal version 2.6.3 ( 71 ). MAGs were classified with GTDB-Tk version 1.3.0 ( 72 ) and by alignment with Silva database version 138 ( 62 ) using mothur version 1.39.5 ( 73 ) in instances where 16 S rRNA gene was recovered by rRNAFinder ( 68 ).…”

Environmental selection influences the microbiome of subsurface petroleum reservoirs

“…To identify potential for microbial degradation of crude oil, functional marker genes encoding enzymes that initiate aerobic or anaerobic hydrocarbon biodegradation, by activating either alkane or aromatic compounds, were examined using a set of 37 newly developed hidden Markov models (Khot et al 2021; Figure 4; Table S7). Of the 28 aerobic and 9 anaerobic marker genes tested, 17 were identified in 16 of the 25 metagenomes.…”

“…Sporulation genes were identified by manual searching for KO numbers of specific marker genes. Genes involved in aerobic and anaerobic activation of hydrocarbon compounds (i.e., indicators of hydrocarbon biodegradation capability) were annotated using the CANT-HYD database of phylogeny-derived hidden Markov models (Khot et al 2021). The 10 CANT-HYD trusted cut-off domain score was used to annotate hydrocarbon activation functions reported in Table S7 and Figure 4.…”

HADEG: A Curated Hydrocarbon Aerobic Degradation Enzymes and Genes Database

“…A more recent database is that of the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), which contains genes involved in aerobic and anaerobic aliphatic and aromatic hydrocarbon degradation pathways. CANT-HYD uses Hidden Markov Models (HMMs) for the annotation of six monophyletic clades of genes related to aliphatic aerobic degradation ( alkB, almA, ladA, bmo , CYP153, prm ), six related to aromatics ( dmp, dsz , MAH, ndo, tmo, tom ), and eight related to anaerobic pathways (Khot et al, 2021). The workflow derives 37 HMMs from experimental and in silico-inferred functional enzymes and is designed for the identification and annotation of marker genes, not including some pathways of hydrocarbon degradation.…”